This paper proposes a new method — using neural oscillators — for filtering out background vibration noise in meshing plastic gear pairs in the detection of signs of gear failure. In this paper these unnecessary frequency components are eliminated with a feed-forward control system in which the neural oscillator’s synchronization property works. Each neural oscillator is designed to tune the natural frequency to a particular one of the components.
This paper presents an original method for computing the loaded mechanical behavior of fiber reinforced polymer gears. Although thermoplastic gears are unsuitable for application transmitting
high torque, adding fibers can significantly increase their performance. The particular case of
polyamide 6 + 30% glass fibers is studied in this paper.